{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "93d0e85a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "notbook\n"
     ]
    }
   ],
   "source": [
    "print(\"notbook\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8270c270",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3 4 5 6 7]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "array = np.array([1,2,3,4,5,6,7])\n",
    "print(array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d89643e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 2  4  6  8 10 12 14]\n"
     ]
    }
   ],
   "source": [
    "print(array*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3123a09b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  },
  "vscode": {
   "interpreter": {
    "hash": "2c4166c4e60205886b39594020a0a92964d0c5302c672db710129f3f2bb29b9f"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
